Quantitative Analyst

JR United Kingdom; Slough; On-site; GBP 50,000 - 70,000; Full time

Job summary

A global investment management firm seeks to hire a candidate for a predictive modeling role within their elite sports trading team in Slough, UK. This position requires advanced skills in statistics and machine learning, as well as expertise in Python and SQL. The successful candidate will develop and implement predictive models, analyze sports data, and collaborate in a fast-paced team environment, pushing the frontiers of sports trading strategies.

Qualifications

• MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
• Developing mathematical models to predict real-world outcomes.
• Proficiency in numerical implementation and computational methods.

Responsibilities

• Utilise advanced statistical techniques and machine learning to build predictive models.
• Analyse sports data to uncover patterns and generate insights.
• Implement robust, scalable model performance in live environments.

Skills

Strong coding skills in Python

Strong coding skills in SQL

Strong communication skills

Mathematics background

Statistics background

Education

MSc or PhD Degree in relevant fields

Job description

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Join a world-class global investment management firm that specialises in sports trading, spanning football, soccer, cricket, and major US sports like the NBA. As part of their elite trading team, you’ll harness advanced statistical techniques and machine learning to build predictive models that shape their trading strategies.

In this role, you’ll drive revenue growth and develop mathematical models to predict the outcomes of sports events.

Responsibilities:

• Utilise advanced statistical techniques and machine learning to build predictive models that shape our trading strategies
• Develop predictive models for sports outcomes using advanced mathematical and statistical techniques.
• Analyse real-world sports data to uncover patterns and generate insights that inform trading strategies.
• Implement and optimise numerical methods to support robust, scalable model performance in live environments.
• Collaborate closely with fellow researchers and developers in a fast-paced, science-driven team environment.
• Continuously innovate and improve modelling approaches to stay competitive in dynamic and data-rich sports markets.

Requirements:

• MSc, PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
• Strong coding skills in Python and SQL
• Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment.
• Strong background in mathematics, statistics, or a related quantitative field
• Experience in developing mathematical models to predict real-world outcomes
• Proficiency in numerical implementation and computational methods

How to Apply:

Please register your interest by sending your CV to Emily Burgess via the Apply link on this page